Relevant bibliographies by topics / Multidimensional encoding

Academic literature on the topic 'Multidimensional encoding'

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Published: 16 July 2024

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Journal articles on the topic "Multidimensional encoding"

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Eurich, Christian W., and Stefan D. Wilke. "Multidimensional Encoding Strategy of Spiking Neurons." Neural Computation 12, no. 7 (July 1, 2000): 1519–29. http://dx.doi.org/10.1162/089976600300015240.

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Neural responses in sensory systems are typically triggered by a multitude of stimulus features. Using information theory, we study the encoding accuracy of a population of stochastically spiking neurons characterized by different tuning widths for the different features. The optimal encoding strategy for representing one feature most accurately consists of narrow tuning in the dimension to be encoded, to increase the single-neuron Fisher information, and broad tuning in all other dimensions, to increase the number of active neurons. Extremely narrow tuning without sufficient receptive field overlap will severely worsen the coding. This implies the existence of an optimal tuning width for the feature to be encoded. Empirically, only a subset of all stimulus features will normally be accessible. In this case, relative encoding errors can be calculated that yield a criterion for the function of a neural population based on the measured tuning curves.
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Pooksombat, Perathorn, Patanee Udomkavanich, and Wittawat Kositwattanarerk. "Multidimensional Fibonacci Coding." Mathematics 10, no. 3 (January 27, 2022): 386. http://dx.doi.org/10.3390/math10030386.

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Fibonacci codes are self-synchronizing variable-length codes that are proven useful for their robustness and compression capability. Asymptotically, these codes provide better compression efficiency as the order of the underlying Fibonacci sequence increases but at the price of the increased suffix length. We propose a circumvention to this problem by introducing higher-dimensional Fibonacci codes for integer vectors. The resulting multidimensional Fibonacci coding is comparable to the classical one in terms of compression; while encoding several numbers all at once for a shared suffix generally results in a shorter codeword, the efficiency takes a backlash when terms from different orders of magnitude are encoded together. In addition, while laying the groundwork for the new encoding scheme, we provide extensive theoretical background and generalize the theorem of Zeckendorf to higher order. As such, our work unifies several variations of Zeckendorf’s theorem while also providing new grounds for its legitimacy.
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Xu, Di Jian, and Jian Kui Zeng. "Multidimensional Waveform Encoding for Oil Spoil Detection." Advanced Materials Research 889-890 (February 2014): 583–86. http://dx.doi.org/10.4028/www.scientific.net/amr.889-890.583.

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In this paper, we present a new algorithm for the signal design in radar whose function is oil spill segmentation, using the minimum description length (MDL) principle and a polygonal active grid. This algorithm is based on two steps: a first partitioning step into homogeneous signals and a second classification step with an automatic thresholding. The obtained method allows one to find a optimal signals for radar.
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Isnardi, M. A. "Multidimensional interpretation of NTSC encoding and decoding." IEEE Transactions on Consumer Electronics 34, no. 1 (1988): 179–93. http://dx.doi.org/10.1109/30.75386.

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Dumez, Jean-Nicolas, and Lucio Frydman. "Multidimensional excitation pulses based on spatiotemporal encoding concepts." Journal of Magnetic Resonance 226 (January 2013): 22–34. http://dx.doi.org/10.1016/j.jmr.2012.10.010.

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Aoi, Mikio C., Valerio Mante, and Jonathan W. Pillow. "Prefrontal cortex exhibits multidimensional dynamic encoding during decision-making." Nature Neuroscience 23, no. 11 (October 5, 2020): 1410–20. http://dx.doi.org/10.1038/s41593-020-0696-5.

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Shrot, Yoav, and Lucio Frydman. "Spatial encoding strategies for ultrafast multidimensional nuclear magnetic resonance." Journal of Chemical Physics 128, no. 5 (February 7, 2008): 052209. http://dx.doi.org/10.1063/1.2834733.

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Fischer, Brian J., Jacob L. Wydick, Christine Köppl, and José L. Peña. "Multidimensional stimulus encoding in the auditory nerve of the barn owl." Journal of the Acoustical Society of America 144, no. 4 (October 2018): 2116–27. http://dx.doi.org/10.1121/1.5056171.

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Shrot, Yoav, and Lucio Frydman. "Spatial/spectral encoding of the spin interactions in ultrafast multidimensional NMR." Journal of Chemical Physics 131, no. 22 (December 14, 2009): 224516. http://dx.doi.org/10.1063/1.3266422.

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Lu, Qing, Zhenguo Lu, Hongzhao Yang, Shenshen Yang, and Yongmin Li. "FPGA-Based Implementation of Multidimensional Reconciliation Encoding in Quantum Key Distribution." Entropy 25, no. 1 (December 31, 2022): 80. http://dx.doi.org/10.3390/e25010080.

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We propose a multidimensional reconciliation encoding algorithm based on a field-programmable gate array (FPGA) with variable data throughput that enables quantum key distribution (QKD) systems to be adapted to different throughput requirements. Using the circulatory structure, data flow in the most complex pipeline operation in the same time interval, which enables the structural multiplexing of the algorithm. We handle the calculation and storage of eight-dimensional matrices cleverly to conserve resources and increase data processing speed. In order to obtain the syndrome more efficiently, we designed a simplified algorithm according to the characteristics of the FPGA and parity-check matrix, which omits the unnecessary operation of matrix multiplication. The simplified algorithm could adapt to different rates. We validated the feasibility and high speed of the algorithm by implementing the multidimensional reconciliation encoding algorithm on a Xilinx Virtex-7 FPGA. Our simulation results show that the maximum throughput could reach 4.88 M symbols/s.
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Book chapters on the topic "Multidimensional encoding"

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Sándor, Viktória, Mathias Bank, Kristina Schinegger, and Stefan Rutzinger. "Collapsing Complexities: Encoding Multidimensional Architecture Models into Images." In Computational Design and Robotic Fabrication, 371–81. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8637-6_32.

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AbstractThe paper details a 3D to 2D encoding method, which can store complex digital 3D models of architecture within a single image. The proposed encoding works in combination with a point cloud notation and a sequential slicing operation where each slice of points is stored as a single row of pixels in the UV space of a 1024 × 1024 image. The performance of the notation system is compared between a StyleGan2 and existing image editing methods and evaluated through the production of new 3D models of houses with material attributes. The uncovered findings maintain the relatively high level of detail stored through the encoding while allowing for innovative ways of form-finding—producing new and unseen 3d models of architectural houses.
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Omar, Mehnuma Tabassum, and K. M. Azharul Hasan. "An Efficient Encoding Scheme for Dynamic Multidimensional Datasets." In Lecture Notes in Computer Science, 517–23. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69900-4_66.

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Hutchinson, Aaron, and Koray Karabina. "A New Encoding Algorithm for a Multidimensional Version of the Montgomery Ladder." In Progress in Cryptology - AFRICACRYPT 2020, 403–22. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51938-4_20.

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Hicks, Jason L., and Jeffrey J. Starns. "Using Multidimensional Encoding and Retrieval Contexts to Enhance Our Understanding of Stochastic Dependence in Source Memory." In Psychology of Learning and Motivation, 101–40. Elsevier, 2015. http://dx.doi.org/10.1016/bs.plm.2014.09.004.

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Messaoud, Riadh Ben, Sabine Loudcher Rabaséda, Rokia Missaoui, and Omar Boussaid. "OLEMAR." In Data Mining and Knowledge Discovery Technologies, 1–35. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-960-1.ch001.

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Data warehouses and OLAP (online analytical processing) provide tools to explore and navigate through data cubes in order to extract interesting information under different perspectives and levels of granularity. Nevertheless, OLAP techniques do not allow the identification of relationships, groupings, or exceptions that could hold in a data cube. To that end, we propose to enrich OLAP techniques with data mining facilities to benefit from the capabilities they offer. In this chapter, we propose an online environment for mining association rules in data cubes. Our environment called OLEMAR (online environment for mining association rules), is designed to extract associations from multidimensional data. It allows the extraction of inter-dimensional association rules from data cubes according to a sum-based aggregate measure, a more general indicator than aggregate values provided by the traditional COUNT measure. In our approach, OLAP users are able to drive a mining process guided by a meta-rule, which meets their analysis objectives. In addition, the environment is based on a formalization, which exploits aggregate measures to revisit the definition of the support and the confidence of discovered rules. This formalization also helps evaluate the interestingness of association rules according to two additional quality measures: lift and loevinger. Furthermore, in order to focus on the discovered associations and validate them, we provide a visual representation based on the graphic semiology principles. Such a representation consists in a graphic encoding of frequent patterns and association rules in the same multidimensional space as the one associated with the mined data cube. We have developed our approach as a component in a general online analysis platform called Miningcubes according to an Apriori-like algorithm, which helps extract inter-dimensional association rules directly from materialized multidimensional structures of data. In order to illustrate the effectiveness and the efficiency of our proposal, we analyze a real-life case study about breast cancer data and conduct performance experimentation of the mining process.
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Telkki, Ville-Veikko. "Fast 2D NMR to Study Microstructures." In Fast 2D Solution-state NMR, 509–28. The Royal Society of Chemistry, 2023. http://dx.doi.org/10.1039/bk9781839168062-00509.

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In addition to standard solution state chemical analysis, NMR spectroscopy is also a powerful method for the studies of microstructures of solid materials. In addition to solid-state NMR, solid materials can be studied by solution state NMR techniques using either inherent or external probe fluids. This chapter is devoted to fast solution state NMR methods for studying microstructures of hard and soft matter. The first part concentrates on methods relying on chemical shift contrast. Particularly, it focuses on 129Xe NMR of xenon gas, which is broadly used in the investigations of porous materials as well as biosensor applications. It describes how spin exchange optical pumping and chemical exchange saturation transfer (CEST) techniques can be exploited to enhance the sensitivity of experiment up to seven orders of magnitude. Furthermore, it explains how CEST spectra can be measured in a single scan using spatial encoding. The second part is devoted to relaxation and diffusion contrast. It elucidates the principles of ultrafast multidimensional relaxation and diffusion experiments and describes how those experiments can be exploited in the studies of porous materials, aggregation of surfactants, intra- and extracellular metabolites in cancer cell suspensions, etc., even with low field single sided NMR devices.
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Sargent, S. "The Listening Styles Profile." In Handbook of Research on Electronic Surveys and Measurements, 334–38. IGI Global, 2007. http://dx.doi.org/10.4018/978-1-59140-792-8.ch045.

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Traditionally, communication scholars have been most concerned with how, when, where, and with whom individuals choose to communicate. While investigating communication events from an encoder perspective is important, it is equally important to investigate communication from a decoder perspective. Many researchers agree that gaining insight into the listening process—how individuals perceive, process, remember and understand oral messages—should enhance our understanding of communication events substantially. There appears to be a good deal of theoretical support for the notion that listening is a multidimensional concept. For example, descriptions of listening constructs such as “appreciative,” “critical,” “discriminative,” and therapeutic” appear throughout the literature. Furthermore, empirical evidence provided by broadly administered listening performance tests highlights considerable individual differences across divergent constructs such as content, relational, and emotional listening. Differences in listening styles reflect attitudes, beliefs, and predispositions about the how, where, when, who, and what of information reception and encoding. Several examples illustrate the diversity of listening styles. Some people prefer listening to factual information or statistics while others favor personal examples and illustrations. Some are more willing to linger on content while others prefer concise and to the point presentations. The Listening Styles Profile (LSP-16) was developed to identify an individual’s predominant listening style (Watson, Barker, & Weaver, 1995). The Listening Styles Profile is a sixteen item inventory designed to assess four distinct listening preferences labeled people, action, content, and time.
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Davis, Karen C., and Ashima Gupta. "Indexing in Data Warhousing." In Data Warehousing and Mining, 1606–22. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-951-9.ch092.

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Bitmap Indexes (BIs) allow fast access to individual attribute values that are needed to answer a query by storing a bit for each distinct value and tuple. A BI is defined for a single attribute and the encodings are based solely on data values; the Property Map (PMap) is a multidimensional indexing technique that precomputes attribute expressions for each tuple and stores the results as bit strings. In order to determine whether the PMap is competitive with BIs, we conduct a performance study of the PMap with the Range Encoded Bit Sliced Index (REBSI) using cost models to simulate storage and query processing costs for different kinds of query types. We identify parameters that have significant effect on index performance and determine situations in which either index is more suitable. These results could be useful for improving the performance of an analytical decision making system.
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Conference papers on the topic "Multidimensional encoding"

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Li, Fuyou, Feng He, Zhen Dong, and Manqing Wu. "MIMO GMTI radar based on multidimensional waveform encoding." In 2017 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2017. http://dx.doi.org/10.1109/icspcc.2017.8242363.

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Dehmel, A. "Encoding multidimensional wavelet coefficients using the generalized zerotree." In Conference Record. Thirty-Fifth Asilomar Conference on Signals, Systems and Computers. IEEE, 2001. http://dx.doi.org/10.1109/acssc.2001.987033.

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Hayat, Alex, Xingxing Xing, Amir Feizpour, and Aephraim M. Steinberg. "Multidimensional Quantum Information Encoding in the Time Domain." In CLEO: Applications and Technology. Washington, D.C.: OSA, 2012. http://dx.doi.org/10.1364/cleo_at.2012.jth1k.6.

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Nepomnyashchy, O. V., I. V. Kochan, M. S. Medvedev, and I. S. Shishkina. "Multidimensional spatial transformation system for streaming media encoding." In VII INTERNATIONAL CONFERENCE “SAFETY PROBLEMS OF CIVIL ENGINEERING CRITICAL INFRASTRUCTURES” (SPCECI2021). AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0125108.

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Krieger, G., N. Gebert, and A. Moreira. "Multidimensional waveform encoding for synthetic aperture radar remote sensing." In IET International Conference on Radar Systems 2007. IEE, 2007. http://dx.doi.org/10.1049/cp:20070482.

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Krieger, Gerhard, Nicolas Gebert, and Alberto Moreira. "Multidimensional waveform encoding for spaceborne synthetic aperture radar systems." In 2007 International Waveform Diversity and Design Conference. IEEE, 2007. http://dx.doi.org/10.1109/wddc.2007.4339427.

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Krieger, Gerhard, Nicolas Gebert, and Alberto Moreira. "Digital beamforming and multidimensional waveform encoding for spaceborne radar remote sensing." In 2007 European Radar Conference. IEEE, 2007. http://dx.doi.org/10.1109/eurad.2007.4404932.

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Decheva, Desislava, and Lars Linsen. "Data Aggregation and Distance Encoding for Interactive Large Multidimensional Data Visualization." In International Conference on Information Visualization Theory and Applications. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006602502250235.

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Alexandru, Roxana, and Pier Luigi Dragotti. "Time encoding and decoding of multidimensional signals with finite rate of innovation." In 2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2021. http://dx.doi.org/10.1109/ieeeconf53345.2021.9723165.

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Chun, Yong, and Jeffrey A. Fessler. "Deep BCD-Net Using Identical Encoding-Decoding CNN Structures for Iterative Image Recovery." In 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP). IEEE, 2018. http://dx.doi.org/10.1109/ivmspw.2018.8448694.

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